Performance of Brazilian credit unions: An analysis from PEARLS indicators

Silva, Alexsandra; Santos, Joséte Florencio dos; Ranciaro Neto, Adhemar

doi:10.1590/1678-6971/eRAMR230057.en

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Resources and Entrepreneurial Development • RAM, Rev. Adm. Mackenzie 24 (1) • 2023 • https://doi.org/10.1590/1678-6971/eRAMR230057.en copy

Performance of Brazilian credit unions: An analysis from PEARLS indicators

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

Purpose:

To explain the performance of Brazilian credit unions, focusing on the institutions with the best segmentation level in the National Financial System (NFS).

Originality/value:

This study used a scenario not yet explored seeking to relate a homogeneous group of unions selected through the NFS segmentation framework and applying financial indexes standardized by the World Council of Credit Unions (Woccu), known as the PEARLS System, to fill, in a practical way, a gap regarding the perspective of identification of factors that impact the performance of Brazilian credit unions.

Design/methodology/approach:

The statistical technique of multiple linear regression was used, operationalized by the ordinary least squares (OLS) method on a balanced panel in the period from 2009 to 2018, modeled with three performance proxies and explained by the Pearls key indexes, with a sample of 81 unions.

Findings:

The main results showed that cooperatives have low rates of profitability and that it is necessary to increase investments in productive assets. Regarding performance, the net loan portfolio (E1) is directly and positively associated with profitability (ROA and ROE) and to the adjusted net equity growth (CPLA). However, default (A1) reflects a tendency to consume the net institutional capital (E9) and compromises the growth of these institutions. Moreover, the credit portfolio is indeed the most valuable asset and one of the most responsible factors for the performance of Brazilian credit unions.

KEYWORDS:
credit unions; performance; PEARLS; Woccu; Bacen

Variable	Measure	Expected sign	Cosif accounts
CPLA (adjusted net equity growth)	${CPLA}_{i} = \frac{{PLA}_{i}}{{PLA}_{i - 1}}$	(+)	[Net equity (6000000-2); income statement creditor accounts (7000000-9); income statement debtor accounts (8000000-6)].
ROA (return on assets)	$ROA = \frac{S}{AT}$	(+)	[Accumulated surplus or loss (61700.00-2)]; [current and long-term assets (1000000-7); permanent (2000000-4)].
ROE (return on equity)	$ROE = \frac{S}{PL}$	(+)	[Accumulated surplus or loss (6170000-2)]; [net equity (6000000-2)].
P1 (protection)	$P 1 = \frac{PE}{TE}$	(-)	[Provision for credit operations (1690000-8)]; [classification of the credit portfolio (3100000-0)].
E1 (effective financial structure)	$E 1 = \frac{EL}{AT}$	(+)	[Credit operations (1600000-1); provision for credit operations (1690000-8)]; [current and long-term assets (1000000-7); permanent (2000000-4)].
E9 (effective financial structure)	$E 9 = \frac{CIL}{AT}$	(+)	[Institutional capital (closing balance); legal reserve (6.1.5.10.00-3); statutory reserves (6.1.5.20.00-0); contingency reserves (6.1.5.30.00-7); FATES (4.9.3.20.00-2); accumulated surplus or loss (61700.00-2)]; [current and long-term assets (1000000-7); permanent (2000000-4)].
A1 (asset quality)	$A 1 = \frac{EA}{TE}$	(-)	[C-level risk operations (31400002); D-level risk operations (31500005); E-level risk operations (31600008); F-level risk operations (31700001); G-level risk operations (31800004); H-level risk operations (31900007)]; [credit portfolio classification (31000000)].
L1 (liquidity)	$L 1 = \frac{IL}{DT}$	(+)	[Availabilities (1100000-6)]; [sight deposits (4110000-0)].

Variable	Mean	Median	Minimum	Maximum	Standard deviation
CPLA	0.2604	0.2190	−1.0000	5.2563	0.2776
ROA	0.0139	0.0145	−0.1083	0.0452	0.0116
ROE	0.0736	0.0856	−0.9920	0.2213	0.0752
P1	0.0584	0.0542	0.0000	0.3131	0.0277
E1	0.5079	0.5161	0.0000	0.7939	0.1070
E9	0.0792	0.0708	−0.1064	0.3863	0.0498
A1	0.2956	0.2745	0.0000	0.9015	0.1585
L1	0.0860	0.0747	0.0000	0.4224	0.0529

Random effect
Variables	CPLA
Variables	Coefficient	p value
P1	−0.1328803	0.834
E1	0.52684***	0.000
E9	−0.71981***	0.019
A1	0.17848***	0.012
L1	−0.1672102	0.382
Constant	0.0192449	0.832
Number of observations		810
R²		0.0692
F/Wald		38.72
Prob. F		0.00
Rho		0.0409
Hausman		0.106

Fixed effect
Variables	ROA		ROE
Variables	Coefficient	p value	Coefficient	p value
P1	−0.08501***	0.003	−0.82655***	0.000
E1	0.02411***	0.010	0.13750**	0.087
E9	0.21710***	0.000	1.11247***	0.004
A1	0.00125	0.726	0.02718	0.206
L1	0.00351	0.665	0.04783	0.411
Constant	−0.01128	0.118	−0.04826	0.455
N		810		810
R²		0.4132		0.1839
F/Wald		8.12		4.54
Prob. F		0.000		0.0011
Rho		0.5594		0.5548
Hausman		0.000		0.001

Variables	CPLA	ROA	ROE
P1	N/A	−0.08501***	−0.,82655***
E1	0.52684***	0.02411***	0.13750**
E9	−0.71981***	0.21710***	1.,11247***
A1	0.17848***	N/A	N/A
L1	N/A	N/A	N/A

Editora Mackenzie; Universidade Presbiteriana Mackenzie Rua da Consolação, 896, Edifício Rev. Modesto Carvalhosa, Térreo - Coordenação da RAM, Consolação - São Paulo - SP - Brasil - cep 01302-907 - São Paulo - SP - Brazil
E-mail: revista.adm@mackenzie.br

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[1] Correspondence concerning this article should be addressed to Joséte Florencio dos Santos, Av. dos Funcionários, s/n, Departamento de Ciências Administrativas da Universidade Federal de Pernambuco, Cidade Universitária, Recife, Pernambuco, Brasil, ZIP code 50740-580. Email: jfs@ufpe.br